{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Multiclass classification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The multiclass classification problem is a regression problem from an input $x \\in {\\cal X}$ to discrete labels $y\\in {\\cal Y}$ where ${\\cal Y}$ is a discrete set of size $C$ bigger than 2 (for $C=2$ it is the more usual binary classification)\n",
    "\n",
    "Labels are encoded in a one-hot fashion, that is if $C=4$ and $y=2$, we note $\\bar{y} = [0,1,0,0]$\n",
    "\n",
    "The generative model for this problem we consider is built of \n",
    " * $C$ latent functions $\\mathbf{f} = [f_1,...,f_C]$ with independent Gaussian Process prior\n",
    " * a determinisctic function building a discrete distribution $\\pi(\\mathbf{f}) = [\\pi_1(f_1),...,\\pi_C(f_C)]$ from the latents such that $\\sum_c \\pi_c(f_c) = 1$. \n",
    " * a Discrete Likelihood $p(y|\\mathbf{f}) = Discrete(y;\\pi(\\mathbf{f})) = \\prod_c \\pi_c(f_c)^{\\bar{y}_c}$\n",
    "\n",
    "A typical example of $\\pi$ is the softmax function \n",
    "\n",
    "$$ \\pi_c (f_c) \\propto \\exp( f_c)$$\n",
    "\n",
    "Another convenient one is the Robust Max\n",
    "$$\n",
    "\\pi_c(\\mathbf{f}) = \\begin{cases} 1 - \\epsilon, & \\mbox{if } c = \\arg \\max_c f_c \\\\\n",
    " \\epsilon /(C-1), & \\mbox{ otherwise} \\end{cases}\n",
    "$$\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-06-13T09:42:54.989725Z",
     "start_time": "2018-06-13T09:42:53.821801Z"
    }
   },
   "outputs": [],
   "source": [
    "import gpflow\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "from gpflow.test_util import notebook_niter\n",
    "from multiclass_classification import plot_posterior_predictions, colors\n",
    "\n",
    "np.random.seed(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sampling from the GP multiclass generative model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Declaring model parameters and input"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-06-13T09:42:55.175406Z",
     "start_time": "2018-06-13T09:42:54.990770Z"
    }
   },
   "outputs": [],
   "source": [
    "# Number of functions and number of data points\n",
    "C = 3\n",
    "N = 100\n",
    "\n",
    "# RBF kernel lengthscale\n",
    "lengthscale = 0.1\n",
    "\n",
    "# Jitter\n",
    "jitter_eye = np.eye(N) * 1e-6\n",
    "\n",
    "# Input\n",
    "X = np.random.rand(N, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Sampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# RBF kernel matrix\n",
    "kern = gpflow.kernels.RBF(1, lengthscales=lengthscale)\n",
    "K = kern.compute_K_symm(X) + jitter_eye\n",
    "\n",
    "# Latents prior sample\n",
    "f = np.random.multivariate_normal(mean=np.zeros(N), cov=K, size=(C)).T\n",
    "\n",
    "# Hard max observation\n",
    "Y = np.argmax(f, 1).reshape(-1,).astype(int)\n",
    "\n",
    "# One-hot encoding\n",
    "Y_hot = np.zeros((N, C), dtype=bool)\n",
    "Y_hot[np.arange(N), Y] = 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "order = np.argsort(X.reshape(-1,))\n",
    "\n",
    "for c in range(C):  \n",
    "    plt.plot(X[order], f[order, c], '.', color=colors[c], label=str(c))\n",
    "    plt.plot(X[order], Y_hot[order, c], '-', color=colors[c])\n",
    "\n",
    "\n",
    "plt.legend()\n",
    "plt.xlabel('$X$')\n",
    "plt.ylabel('Latent (dots) and one-hot labels (lines)')\n",
    "plt.title('Sample from the joint $p(Y, \\mathbf{f})$')\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Inference\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Inference here consists in computing the posterior distribution over the latent functions given the data $p(\\mathbf{f}|Y, X)$.\n",
    "\n",
    "Different inference methods may be used. We here perform variational inference.\n",
    "A treatment of the multiclass classification problem using MCMC sampling may be found in the [MCMC notebook](../advanced/mcmc.ipynb).\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Approximate inference: Sparse Variational Gaussian Process"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Declaring the SVGP model (See the [GPs for big data](../advanced/gps_for_big_data.ipynb) notebook)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>class</th>\n",
       "      <th>prior</th>\n",
       "      <th>transform</th>\n",
       "      <th>trainable</th>\n",
       "      <th>shape</th>\n",
       "      <th>fixed_shape</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SVGP/feature/Z</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>None</td>\n",
       "      <td>(none)</td>\n",
       "      <td>False</td>\n",
       "      <td>(20, 1)</td>\n",
       "      <td>True</td>\n",
       "      <td>[[0.5488135039273248], [0.6458941130666561], [...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SVGP/kern/kernels/0/lengthscales</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>None</td>\n",
       "      <td>+ve</td>\n",
       "      <td>True</td>\n",
       "      <td>()</td>\n",
       "      <td>True</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SVGP/kern/kernels/0/variance</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>None</td>\n",
       "      <td>+ve</td>\n",
       "      <td>True</td>\n",
       "      <td>()</td>\n",
       "      <td>True</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SVGP/kern/kernels/1/variance</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>None</td>\n",
       "      <td>+ve</td>\n",
       "      <td>False</td>\n",
       "      <td>()</td>\n",
       "      <td>True</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SVGP/likelihood/invlink/epsilon</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>Beta(0.2,5.0)</td>\n",
       "      <td>[0.0, 1.0]</td>\n",
       "      <td>False</td>\n",
       "      <td>()</td>\n",
       "      <td>True</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SVGP/q_mu</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>None</td>\n",
       "      <td>(none)</td>\n",
       "      <td>True</td>\n",
       "      <td>(20, 3)</td>\n",
       "      <td>True</td>\n",
       "      <td>[[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SVGP/q_sqrt</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>None</td>\n",
       "      <td>+ve</td>\n",
       "      <td>True</td>\n",
       "      <td>(20, 3)</td>\n",
       "      <td>True</td>\n",
       "      <td>[[1.0, 1.0, 1.0], [1.0, 1.0, 1.0], [1.0, 1.0, ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      class          prior   transform  \\\n",
       "SVGP/feature/Z                    Parameter           None      (none)   \n",
       "SVGP/kern/kernels/0/lengthscales  Parameter           None         +ve   \n",
       "SVGP/kern/kernels/0/variance      Parameter           None         +ve   \n",
       "SVGP/kern/kernels/1/variance      Parameter           None         +ve   \n",
       "SVGP/likelihood/invlink/epsilon   Parameter  Beta(0.2,5.0)  [0.0, 1.0]   \n",
       "SVGP/q_mu                         Parameter           None      (none)   \n",
       "SVGP/q_sqrt                       Parameter           None         +ve   \n",
       "\n",
       "                                  trainable    shape  fixed_shape  \\\n",
       "SVGP/feature/Z                        False  (20, 1)         True   \n",
       "SVGP/kern/kernels/0/lengthscales       True       ()         True   \n",
       "SVGP/kern/kernels/0/variance           True       ()         True   \n",
       "SVGP/kern/kernels/1/variance          False       ()         True   \n",
       "SVGP/likelihood/invlink/epsilon       False       ()         True   \n",
       "SVGP/q_mu                              True  (20, 3)         True   \n",
       "SVGP/q_sqrt                            True  (20, 3)         True   \n",
       "\n",
       "                                                                              value  \n",
       "SVGP/feature/Z                    [[0.5488135039273248], [0.6458941130666561], [...  \n",
       "SVGP/kern/kernels/0/lengthscales                                                1.0  \n",
       "SVGP/kern/kernels/0/variance                                                    1.0  \n",
       "SVGP/kern/kernels/1/variance                                                   0.01  \n",
       "SVGP/likelihood/invlink/epsilon                                               0.001  \n",
       "SVGP/q_mu                         [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, ...  \n",
       "SVGP/q_sqrt                       [[1.0, 1.0, 1.0], [1.0, 1.0, 1.0], [1.0, 1.0, ...  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sum kernel: Matern32 + White\n",
    "kern = gpflow.kernels.Matern32(1) + gpflow.kernels.White(1, variance=0.01)\n",
    "\n",
    "# Robustmax Multiclass Likelihood\n",
    "invlink = gpflow.likelihoods.RobustMax(C)  # Robustmax inverse link function\n",
    "likelihood = gpflow.likelihoods.MultiClass(3, invlink=invlink)  # Multiclass likelihood\n",
    "Z = X[::5].copy()  # inducing inputs\n",
    "\n",
    "m = gpflow.models.SVGP(\n",
    "    X, Y, kern=kern, likelihood=likelihood,\n",
    "    Z=Z, num_latent=C, whiten=True, q_diag=True)\n",
    "\n",
    "# Only train the variational parameters\n",
    "m.kern.kernels[1].variance.trainable = False\n",
    "m.feature.trainable = False\n",
    "m.as_pandas_table()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Running inference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Optimization terminated with:\n",
      "  Message: b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'\n",
      "  Objective function value: 61.366270\n",
      "  Number of iterations: 610\n",
      "  Number of functions evaluations: 687\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Optimization terminated with:\n",
      "  Message: b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'\n",
      "  Objective function value: 61.366270\n",
      "  Number of iterations: 610\n",
      "  Number of functions evaluations: 687\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Optimization terminated with:\n",
      "  Message: b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'\n",
      "  Objective function value: 61.366270\n",
      "  Number of iterations: 1\n",
      "  Number of functions evaluations: 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Optimization terminated with:\n",
      "  Message: b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'\n",
      "  Objective function value: 61.366270\n",
      "  Number of iterations: 1\n",
      "  Number of functions evaluations: 3\n"
     ]
    }
   ],
   "source": [
    "opt = gpflow.train.ScipyOptimizer(options={'maxls': 30,'ftol':1e-10, 'disp':False})\n",
    "#for _ in range(2):\n",
    "opt.minimize(m, maxiter=notebook_niter(1000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_posterior_predictions(m)"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
